Practical Resource Provisioning and Caching with Dynamic Resilience for Cloud-Based Content Distribution Networks
Issue No. 08 - Aug. (2014 vol. 25)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TPDS.2013.287
Menglan Hu , School of Computer Engineering, Nanyang Technological University, Singapore
Jun Luo , School of Computer Engineering, Nanyang Technological University, Singapore
Yang Wang , Faculty of Computer Science, University of New Brunswick, Fredetricton, Canada
Bharadwaj Veeravalli , Department of Electrical and Computer Engineering, National University of Singapore, Singapore
Content distribution networks (CDNs) built on clouds have recently started to emerge. Compared to conventional CDNs, cloud-based CDNs have the benefit of cost efficient hosting services without owning infrastructure. However, resource provisioning and replica placement in cloud CDNs involve a number of challenging issues, mainly due to the dynamic nature of demand patterns. To deal with this dynamic nature, this paper proposes a set of novel algorithms to solve the joint problem of resource provisioning and caching (i.e., replica placement) for cloud-based CDNs with an emphasis on handling the dynamic demand patterns. Firstly, we propose a provisioning and caching algorithm framework called Differential Provisioning and Caching (DPC) algorithm, which aims to rent cloud resources to build CDNs and whereby to cache contents so that the total rental cost can be minimized while all demands are served. DPC consists of 2 steps. Step 1 first maximizes total demands supported by unexpired resources. Then, step 2 minimizes the total rental cost for new resources to serve all remaining demands. For each step we design both greedy and iterative heuristics, each with different advantages over the existing approaches. Moreover, to dynamically adjusts the placement of contents and route maps, we further propose the Caching and Request Balancing (CRB) algorithm, which is light-weight and thus can be frequently executed as a companion of DPC to maximize the total demands. Performance evaluation results are presented to demonstrate the effectiveness and competitiveness of our approaches when compared to existing algorithms.
Bandwidth, Heuristic algorithms, Algorithm design and analysis, Quality of service, Servers, Videos, Dynamic scheduling
M. Hu, J. Luo, Y. Wang and B. Veeravalli, "Practical Resource Provisioning and Caching with Dynamic Resilience for Cloud-Based Content Distribution Networks," in IEEE Transactions on Parallel & Distributed Systems, vol. 25, no. 8, pp. 2169-2179, 2014.